Soil microbial community characterization is increasingly being used to determine the responses of soils to stress and disturbances and to assess ecosystem sustainability. However, there is little experimental evidence to indicate that predictable patterns in microbial community structure or composition occur during secondary succession or ecosystem restoration. This study utilized a chronosequence of developing jarrah (Eucalyptus marginata) forest ecosystems, rehabilitated after bauxite mining (up to 18 years old), to examine changes in soil bacterial and fungal community structures (by automated ribosomal intergenic spacer analysis [ARISA]) and changes in specific soil bacterial phyla by 16S rRNA gene microarray analysis. This study demonstrated that mining in these ecosystems significantly altered soil bacterial and fungal community structures. The hypothesis that the soil microbial community structures would become more similar to those of the surrounding nonmined forest with rehabilitation age was broadly supported by shifts in the bacterial but not the fungal community. Microarray analysis enabled the identification of clear successional trends in the bacterial community at the phylum level and supported the finding of an increase in similarity to nonmined forest soil with rehabilitation age. Changes in soil microbial community structure were significantly related to the size of the microbial biomass as well as numerous edaphic variables (including pH and C, N, and P nutrient concentrations). These findings suggest that soil bacterial community dynamics follow a pattern in developing ecosystems that may be predictable and can be conceptualized as providing an integrated assessment of numerous edaphic variables.

We present a new model for the soil-water retention curve, (h m ), which, in contrast to earlier models, anchors the curve at zero water content and does away with the unspecified residual water content. The proposed equation covers the complete retention curve, with the pressure head, h m , stretching over approximately seven orders of magnitude. We review the concept of pF from its origin in the papers of Schofield and discuss what Schofield meant by the 'free energy, F'. We deal with (historical) criticisms regarding the use of the log scale of the pressure head, which, unfortunately, led to the apparent demise of the pF. We espouse the advantages of using the log scale in a model for which the pF is the independent variable, and we present a method to deal with the problem of the saturated water content on the semi-log graph being located at a pF of minus infinity. Where a smaller range of the water retention is being considered, the model also gives an excellent fit on a linear scale using the pressure head, h m , itself as the independent variable. We applied the model to pF curves found in the literature for a great variety of soil textures ranging from dune-sand to river-basin clay. We found the equation for the model to be capable of fitting the pF curves with remarkable success over the complete range from saturation to oven dryness. However, because interest generally lies in the plant-available water range (i.e. saturation, y s , to wilting point, y wp ), the following relation, which can be plotted on a linear scale, is sufficient for most purposes: ðh m Þ ¼ wp þ k 1 fexpðÀk 0 =15 000 n Þ À expðÀk 0 =h n m Þg, where k 0 , k 1 and n are adjustable fitting parameters.

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Alcoa World Alumina Australia has been rehabilitating bauxite mines in the jarrah (Eucalyptus marginata) forest of western Australia for more than 35 years. Completion criteria were developed in the 1990s for native species rehabilitation, with various desirable characteristics described as the rehabilitation ages. Successional models can be useful in mining rehabilitation for predicting whether sites are developing along the desired trajectory toward the rehabilitation objective. The current rehabilitation objective is to establish a self-sustaining jarrah forest ecosystem, planned to enhance or maintain water, timber, recreation, and conservation values. The major objective of this study was to present a state-and-transition successional model that assists Alcoa to identify sites that will and will not meet identified completion criteria. Agreed completion criteria and vegetation data collected from native species rehabilitation from 9 months to 15 years old were used to construct a state-and-transition model. The model identified the various desired and deviated successional states and factors that cause transitions between these states. Five desirable and nine deviated states were identified and described in detail. Key indicators relating to desired and deviated states include eucalypt density, species richness, legume density, topsoil cover, vegetation structure, ripping depth, and tree health and form. Identified management manipulations to return deviated states to the desired successional trajectory include ripping, reseeding, replanting, weed control, and tree thinning. Some of the identified thresholds between desired and deviated states will require significant management input (e.g., reripping), whereas others require little or no input (e.g., recovery following wildfire). Of the 6,429 ha of native species rehabilitation undertaken between 1991 and 2002, 98% is on or above the desired successional trajectory. More than half of the rehabilitated area is regarded as being above the desired trajectory because of high tree density. Although these sites meet the existing completion criteria, management input may be required in the future, emphasizing the importance of identifying maximum and minimum completion criteria. The state-and-transition model of successional development is a practical but rigorous land management tool that has the potential to be applied in a wide variety of ecosystems and wide range of land uses.